Conversation across continents on hierarchies, human security and COVID-19
Bibliographic record
Abstract
Life as we knew it has changed with the COVID-19 global pandemic disrupting every nation. Navigating engagement in daily living entails shifts in habits, roles and routines. The sense of self is reimagined, challenged and reflected upon, cradled within health and social care systems masking human rights and social justice. For some there is freedom, calmness, greater connectivity and collegiality, and for others, there is entrapment, fear, disorientation, emotional distress, occupational deprivation and isolation. This chapter explores daily living disruption by engaging scholars from across five continents in co-designing through conversation, by discussing individual and collective experiences of disability hierarchies and human security during the COVID-19 pandemic. Consideration is given to the heterogeneity of lives and in-country contexts (Australia, India, Africa, Ireland and Canada). Perspectives from experts through lived experiences and academics are shared, drawing on human rights, capability and disability theories; global health and COVID-19 policy; and author observations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.026 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".